Application of MJO Simulation Diagnostics to Climate Models

By Daehyun Kim, K. Sperber, William F. Stern, Duane Waliser, I. Kang, E. Maloney, Wanqiu Wang, K. Weickmann, James Joseph Benedict, M. Khairoutdinov and 5 more. 2009

396 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/bd5a2ffd53690f21d08277b44b22ac4dcbb42d43

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Citations in the corpus

CORRIGENDUM of the MJO Transition from Shallow to Deep Convection in Cloudsat-Calipso Data and GISS GCM Simulations (2012, background): “…models that have a tighter link between convection and humidity because of strong convective entrainment or rain evaporation (Bechtold et al. 2008; Kim et al. 2009, 2011a; Hannah and Maloney 2011) or that embed a cloud-resolving model within GCM gridboxes (Khairoutdinov et al. 2008; Thayer-Calder…”
MJO and Convectively Coupled Equatorial Waves Simulated by CMIP5 Climate Models (2013, background): “…precipitation (Fu and Wang 2009; Seo and Wang 2010), the vertical heating proﬁle (Li et al. 2009), convective momentum transport (Deng and Wu 2010; Zhou et al. 2012), cloud–radiation feedback (Lin et al. 2007; Kim et al. 2011a), and the time-mean state (Sperber and Annamalai 2008; Kim et al. 2009).”
A Unified Convection Scheme (UNICON). Part I: Formulation (2014, background): “Some GCMs showed progress in suppressing the double ITCZ (Song and Zhang 2009; Chikira and Sugiyama 2010;Watanabe et al. 2010) or simulating theMJO (Kim et al. 2009; Chikira and Sugiyama 2013).”
Structure of the Madden-Julian Oscillation in the Superparameterized CAM (2009, background): “These simulated convective biases are likely due to several factors including unrealistic boundary layer interactions, a lack of weakening of the simulated disturbance over the Maritime Continent, and mean state differences.”
Atmosphere‐ocean coupled processes in the Madden‐Julian oscillation (2015, methodology): “Time series of the net surface heat flux (radiative, latent heat, and sensible heat fluxes), precipitation, wind stress, and SST during DYNAMO and TOGA COARE are shown in Figures 2 and 3.”
MJO simulation in CMIP5 climate models: MJO skill metrics and process-oriented diagnosis (2017, positive): “…power ratio (E/W ratio hereafter), indicates the robustness of eastward propagating feature of the MJO (Zhang and Hendon 1997) and has been frequently used in observational (e.g., Zhang and Hendon 1997; Hendon et al. 1999) and modeling studies (e.g., Lin et al. 2006; Kim et al. 2009).”
Role of the Boundary Layer Moisture Asymmetry in Causing the Eastward Propagation of the Madden-Julian Oscillation* (2012, background): “It is found that heating-induced free-atmospheric wave dynamics account for 75%–90% of the total PBL convergence, while the warm SST anomaly induced by air–sea interaction contributes 10%–25% of the total PBL convergence.”
The Role of Convective Moistening in the Madden–Julian Oscillation (2009, methodology): “This method has also been used to analyze profiles of the equatorial Indian Ocean and Western Pacific by Thayer-Calder (2008) and Kim et al. (2009).”